A wavelet based algorithm for Ocular Artifact detection In the EEG signals

Abstract

Artifacts are noises introduced to an electroencephalogram (EEG) signal by patient's movements. Eye-blinks and movements of the eyeballs produce electrical signals that are collectively known as Ocular Artifacts (OA) and these are 10-100 times stronger than EEG signal which is being recorded. Removing artifacts from EEG signal may aid the work of doctors, because artifacts disturb their attention. This paper present a new method to automatically identify the position of Ocular Artifacts zones in contaminated EEG signal. Then only removing it's to obtain clean EEG based on the stationary wavelet transform (SWT). In this case, correlation coefficient between wavelet coefficients of the Ocular Artifacts zones in contaminated EEG signal and same zones in electrooculogram (EOG) will be used to generate the wavelet coefficients for artifact-free EEG signal.